Geographic space, as the arena within which all of the natural and social processes occur, and time, have become key research components of social science for the past two decades. However, most GIS software packages lack the predictive and analytic capabilities for complex problems, such as spatial statistical methods and spatial modeling. Meanwhile, the spatio-temporally explicit representation of complex, heterogeneous and dynamic geographic data sets is a particularly challenging issue. Many efforts have been made in developing tools for effective representation of health data, spatio-temporal analysis of the data, and the dynamic process simulation of disease transmission. To meet this demand, we attempted to develop a tool for integrating spatio-temporal analysis, simulation and representation of health data and processes. In this paper, we will introduce some methods for spatial temporal data analysis and their applications in public health. We'll describe the conceptual model of spatial temporal process simulation and the process-oriented spatio-temporal data model adopted in the tool we developed. After that, we'll present the framework of our integrated research toolkit, and demonstrate how to conduct analysis, modeling, and simulation with this software. Finally, we will discuss some issues for future studies.